print('hello')[1] "hello"
The following machine learning project focuses on…
print('hello')[1] "hello"
# Python code
import numpy as np
print(np.mean([10, 20, 30, 40, 50]))30.0
library(here)
directory <- here("data")
properties <- read.csv(file.path(directory,"properties.csv"))
metrecarré <- read.csv(file.path(directory,"snb-data-plimoincha-fr-all-20240321_0900.csv"))
# Assuming your data frame is named metrecarré
metrecarré <- metrecarré[-1, ]
split_data <- lapply(metrecarré, function(x) unlist(strsplit(as.character(x), ";")))
split_df <- do.call(rbind, split_data)Warning in (function (..., deparse.level = 1) : number of columns of result is
not a multiple of vector length (arg 2)
#install.packages("readxl")
library(readxl)
# Read the cpi file
cpi_data_excel <- read_excel(file.path(directory,"cpi.xlsx"))Warning: Expecting numeric in B4 / R4C2: got a date
Warning: Expecting numeric in C4 / R4C3: got a date
Warning: Expecting numeric in D4 / R4C4: got a date
Warning: Expecting numeric in E4 / R4C5: got a date
Warning: Expecting numeric in F4 / R4C6: got a date
Warning: Expecting numeric in G4 / R4C7: got a date
Warning: Expecting numeric in H4 / R4C8: got a date
Warning: Coercing numeric to date in I1024 / R1024C9
Warning: Coercing numeric to date in I1025 / R1025C9
Warning: Coercing numeric to date in I1026 / R1026C9
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Warning: Coercing numeric to date in J1086 / R1086C10
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Warning: Coercing numeric to date in J1087 / R1087C10
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Warning: Coercing numeric to date in J1120 / R1120C10
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Warning: Coercing numeric to date in J1121 / R1121C10
Warning: Coercing numeric to date in I1122 / R1122C9
Warning: Coercing numeric to date in J1122 / R1122C10
Warning: Coercing numeric to date in I1123 / R1123C9
Warning: Coercing numeric to date in J1123 / R1123C10
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Warning: Coercing numeric to date in I1125 / R1125C9
Warning: Coercing numeric to date in J1125 / R1125C10
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Warning: Coercing numeric to date in J1126 / R1126C10
Warning: Coercing numeric to date in I1127 / R1127C9
Warning: Coercing numeric to date in J1127 / R1127C10
Warning: Coercing numeric to date in I1128 / R1128C9
Warning: Coercing numeric to date in J1128 / R1128C10
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Warning: Coercing numeric to date in J1129 / R1129C10
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Warning: Coercing numeric to date in J1130 / R1130C10
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Warning: Coercing numeric to date in I1132 / R1132C9
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Warning: Coercing numeric to date in J1136 / R1136C10
Warning: Coercing numeric to date in I1137 / R1137C9
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Warning: Coercing numeric to date in J1138 / R1138C10
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Warning: Coercing numeric to date in J1139 / R1139C10
Warning: Coercing numeric to date in I1140 / R1140C9
Warning: Coercing numeric to date in J1140 / R1140C10
Warning: Coercing numeric to date in I1141 / R1141C9
Warning: Coercing numeric to date in J1141 / R1141C10
Warning: Coercing numeric to date in I1142 / R1142C9
Warning: Coercing numeric to date in J1142 / R1142C10
Warning: Coercing numeric to date in I1143 / R1143C9
Warning: Coercing numeric to date in J1143 / R1143C10
Warning: Coercing numeric to date in I1144 / R1144C9
Warning: Coercing numeric to date in J1144 / R1144C10
Warning: Coercing numeric to date in K1144 / R1144C11
Warning: Coercing numeric to date in I1145 / R1145C9
Warning: Coercing numeric to date in J1145 / R1145C10
Warning: Coercing numeric to date in K1145 / R1145C11
Warning: Coercing numeric to date in I1146 / R1146C9
Warning: Coercing numeric to date in J1146 / R1146C10
Warning: Coercing numeric to date in K1146 / R1146C11
Warning: Coercing numeric to date in I1147 / R1147C9
Warning: Coercing numeric to date in J1147 / R1147C10
Warning: Coercing numeric to date in K1147 / R1147C11
Warning: Coercing numeric to date in I1148 / R1148C9
Warning: Coercing numeric to date in J1148 / R1148C10
Warning: Coercing numeric to date in K1148 / R1148C11
Warning: Coercing numeric to date in I1149 / R1149C9
Warning: Coercing numeric to date in J1149 / R1149C10
Warning: Coercing numeric to date in K1149 / R1149C11
Warning: Coercing numeric to date in I1150 / R1150C9
Warning: Coercing numeric to date in J1150 / R1150C10
Warning: Coercing numeric to date in K1150 / R1150C11
Warning: Coercing numeric to date in I1151 / R1151C9
Warning: Coercing numeric to date in J1151 / R1151C10
Warning: Coercing numeric to date in K1151 / R1151C11
Warning: Coercing numeric to date in I1152 / R1152C9
Warning: Coercing numeric to date in J1152 / R1152C10
Warning: Coercing numeric to date in K1152 / R1152C11
Warning: Coercing numeric to date in I1153 / R1153C9
Warning: Coercing numeric to date in J1153 / R1153C10
Warning: Coercing numeric to date in K1153 / R1153C11
Warning: Coercing numeric to date in I1154 / R1154C9
Warning: Coercing numeric to date in J1154 / R1154C10
Warning: Coercing numeric to date in K1154 / R1154C11
Warning: Coercing numeric to date in I1155 / R1155C9
Warning: Coercing numeric to date in J1155 / R1155C10
Warning: Coercing numeric to date in K1155 / R1155C11
Warning: Coercing numeric to date in I1156 / R1156C9
Warning: Coercing numeric to date in J1156 / R1156C10
Warning: Coercing numeric to date in K1156 / R1156C11
Warning: Coercing numeric to date in I1157 / R1157C9
Warning: Coercing numeric to date in J1157 / R1157C10
Warning: Coercing numeric to date in K1157 / R1157C11
Warning: Coercing numeric to date in I1158 / R1158C9
Warning: Coercing numeric to date in J1158 / R1158C10
Warning: Coercing numeric to date in K1158 / R1158C11
Warning: Coercing numeric to date in I1159 / R1159C9
Warning: Coercing numeric to date in J1159 / R1159C10
Warning: Coercing numeric to date in K1159 / R1159C11
Warning: Coercing numeric to date in I1160 / R1160C9
Warning: Coercing numeric to date in J1160 / R1160C10
Warning: Coercing numeric to date in K1160 / R1160C11
Warning: Coercing numeric to date in I1161 / R1161C9
Warning: Coercing numeric to date in J1161 / R1161C10
Warning: Coercing numeric to date in K1161 / R1161C11
Warning: Coercing numeric to date in I1162 / R1162C9
Warning: Coercing numeric to date in J1162 / R1162C10
Warning: Coercing numeric to date in K1162 / R1162C11
Warning: Coercing numeric to date in I1163 / R1163C9
Warning: Coercing numeric to date in J1163 / R1163C10
Warning: Coercing numeric to date in K1163 / R1163C11
Warning: Coercing numeric to date in I1164 / R1164C9
Warning: Coercing numeric to date in J1164 / R1164C10
Warning: Coercing numeric to date in K1164 / R1164C11
Warning: Coercing numeric to date in I1165 / R1165C9
Warning: Coercing numeric to date in J1165 / R1165C10
Warning: Coercing numeric to date in K1165 / R1165C11
Warning: Coercing numeric to date in I1166 / R1166C9
Warning: Coercing numeric to date in J1166 / R1166C10
Warning: Coercing numeric to date in K1166 / R1166C11
Warning: Coercing numeric to date in I1167 / R1167C9
Warning: Coercing numeric to date in J1167 / R1167C10
Warning: Coercing numeric to date in K1167 / R1167C11
Warning: Coercing numeric to date in I1168 / R1168C9
Warning: Coercing numeric to date in J1168 / R1168C10
Warning: Coercing numeric to date in K1168 / R1168C11
Warning: Coercing numeric to date in I1169 / R1169C9
Warning: Coercing numeric to date in J1169 / R1169C10
Warning: Coercing numeric to date in K1169 / R1169C11
Warning: Coercing numeric to date in I1170 / R1170C9
Warning: Coercing numeric to date in J1170 / R1170C10
Warning: Coercing numeric to date in K1170 / R1170C11
Warning: Coercing numeric to date in I1171 / R1171C9
Warning: Coercing numeric to date in J1171 / R1171C10
Warning: Coercing numeric to date in K1171 / R1171C11
Warning: Coercing numeric to date in I1172 / R1172C9
Warning: Coercing numeric to date in J1172 / R1172C10
Warning: Coercing numeric to date in K1172 / R1172C11
Warning: Coercing numeric to date in I1173 / R1173C9
Warning: Coercing numeric to date in J1173 / R1173C10
Warning: Coercing numeric to date in K1173 / R1173C11
Warning: Coercing numeric to date in I1174 / R1174C9
Warning: Coercing numeric to date in J1174 / R1174C10
Warning: Coercing numeric to date in K1174 / R1174C11
Warning: Coercing numeric to date in I1175 / R1175C9
Warning: Coercing numeric to date in J1175 / R1175C10
Warning: Coercing numeric to date in K1175 / R1175C11
Warning: Coercing numeric to date in I1176 / R1176C9
Warning: Coercing numeric to date in J1176 / R1176C10
Warning: Coercing numeric to date in K1176 / R1176C11
Warning: Coercing numeric to date in I1177 / R1177C9
Warning: Coercing numeric to date in J1177 / R1177C10
Warning: Coercing numeric to date in K1177 / R1177C11
Warning: Coercing numeric to date in I1178 / R1178C9
Warning: Coercing numeric to date in J1178 / R1178C10
Warning: Coercing numeric to date in K1178 / R1178C11
Warning: Coercing numeric to date in I1179 / R1179C9
Warning: Coercing numeric to date in J1179 / R1179C10
Warning: Coercing numeric to date in K1179 / R1179C11
Warning: Coercing numeric to date in I1180 / R1180C9
Warning: Coercing numeric to date in J1180 / R1180C10
Warning: Coercing numeric to date in K1180 / R1180C11
Warning: Coercing numeric to date in I1181 / R1181C9
Warning: Coercing numeric to date in J1181 / R1181C10
Warning: Coercing numeric to date in K1181 / R1181C11
Warning: Coercing numeric to date in I1182 / R1182C9
Warning: Coercing numeric to date in J1182 / R1182C10
Warning: Coercing numeric to date in K1182 / R1182C11
Warning: Coercing numeric to date in I1183 / R1183C9
Warning: Coercing numeric to date in J1183 / R1183C10
Warning: Coercing numeric to date in K1183 / R1183C11
Warning: Coercing numeric to date in I1184 / R1184C9
Warning: Coercing numeric to date in J1184 / R1184C10
Warning: Coercing numeric to date in K1184 / R1184C11
Warning: Coercing numeric to date in I1185 / R1185C9
Warning: Coercing numeric to date in J1185 / R1185C10
Warning: Coercing numeric to date in K1185 / R1185C11
Warning: Coercing numeric to date in I1186 / R1186C9
Warning: Coercing numeric to date in J1186 / R1186C10
Warning: Coercing numeric to date in K1186 / R1186C11
Warning: Coercing numeric to date in I1187 / R1187C9
Warning: Coercing numeric to date in J1187 / R1187C10
Warning: Coercing numeric to date in K1187 / R1187C11
Warning: Coercing numeric to date in I1188 / R1188C9
Warning: Coercing numeric to date in J1188 / R1188C10
Warning: Coercing numeric to date in K1188 / R1188C11
Warning: Coercing numeric to date in I1189 / R1189C9
Warning: Coercing numeric to date in J1189 / R1189C10
Warning: Coercing numeric to date in K1189 / R1189C11
Warning: Coercing numeric to date in I1190 / R1190C9
Warning: Coercing numeric to date in J1190 / R1190C10
Warning: Coercing numeric to date in K1190 / R1190C11
Warning: Coercing numeric to date in I1191 / R1191C9
Warning: Coercing numeric to date in J1191 / R1191C10
Warning: Coercing numeric to date in K1191 / R1191C11
Warning: Coercing numeric to date in I1192 / R1192C9
Warning: Coercing numeric to date in J1192 / R1192C10
Warning: Coercing numeric to date in K1192 / R1192C11
Warning: Coercing numeric to date in I1193 / R1193C9
Warning: Coercing numeric to date in J1193 / R1193C10
Warning: Coercing numeric to date in K1193 / R1193C11
Warning: Coercing numeric to date in I1194 / R1194C9
Warning: Coercing numeric to date in J1194 / R1194C10
Warning: Coercing numeric to date in K1194 / R1194C11
Warning: Coercing numeric to date in I1195 / R1195C9
Warning: Coercing numeric to date in J1195 / R1195C10
Warning: Coercing numeric to date in K1195 / R1195C11
Warning: Coercing numeric to date in I1196 / R1196C9
Warning: Coercing numeric to date in J1196 / R1196C10
Warning: Coercing numeric to date in K1196 / R1196C11
Warning: Coercing numeric to date in I1197 / R1197C9
Warning: Coercing numeric to date in J1197 / R1197C10
Warning: Coercing numeric to date in K1197 / R1197C11
Warning: Coercing numeric to date in I1198 / R1198C9
Warning: Coercing numeric to date in J1198 / R1198C10
Warning: Coercing numeric to date in K1198 / R1198C11
Warning: Coercing numeric to date in I1199 / R1199C9
Warning: Coercing numeric to date in J1199 / R1199C10
Warning: Coercing numeric to date in K1199 / R1199C11
Warning: Coercing numeric to date in I1200 / R1200C9
Warning: Coercing numeric to date in J1200 / R1200C10
Warning: Coercing numeric to date in K1200 / R1200C11
Warning: Coercing numeric to date in I1201 / R1201C9
Warning: Coercing numeric to date in J1201 / R1201C10
Warning: Coercing numeric to date in K1201 / R1201C11
Warning: Coercing numeric to date in I1202 / R1202C9
Warning: Coercing numeric to date in J1202 / R1202C10
Warning: Coercing numeric to date in K1202 / R1202C11
Warning: Coercing numeric to date in I1203 / R1203C9
Warning: Coercing numeric to date in J1203 / R1203C10
Warning: Coercing numeric to date in K1203 / R1203C11
Warning: Coercing numeric to date in I1204 / R1204C9
Warning: Coercing numeric to date in J1204 / R1204C10
Warning: Coercing numeric to date in K1204 / R1204C11
Warning: Coercing numeric to date in L1204 / R1204C12
Warning: Coercing numeric to date in I1205 / R1205C9
Warning: Coercing numeric to date in J1205 / R1205C10
Warning: Coercing numeric to date in K1205 / R1205C11
Warning: Coercing numeric to date in L1205 / R1205C12
Warning: Coercing numeric to date in I1206 / R1206C9
Warning: Coercing numeric to date in J1206 / R1206C10
Warning: Coercing numeric to date in K1206 / R1206C11
Warning: Coercing numeric to date in L1206 / R1206C12
Warning: Coercing numeric to date in I1207 / R1207C9
Warning: Coercing numeric to date in J1207 / R1207C10
Warning: Coercing numeric to date in K1207 / R1207C11
Warning: Coercing numeric to date in L1207 / R1207C12
Warning: Coercing numeric to date in I1208 / R1208C9
Warning: Coercing numeric to date in J1208 / R1208C10
Warning: Coercing numeric to date in K1208 / R1208C11
Warning: Coercing numeric to date in L1208 / R1208C12
Warning: Coercing numeric to date in I1209 / R1209C9
Warning: Coercing numeric to date in J1209 / R1209C10
Warning: Coercing numeric to date in K1209 / R1209C11
Warning: Coercing numeric to date in L1209 / R1209C12
Warning: Coercing numeric to date in I1210 / R1210C9
Warning: Coercing numeric to date in J1210 / R1210C10
Warning: Coercing numeric to date in K1210 / R1210C11
Warning: Coercing numeric to date in L1210 / R1210C12
Warning: Coercing numeric to date in I1211 / R1211C9
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New names:
• `` -> `...2`
• `` -> `...3`
• `` -> `...4`
• `` -> `...5`
• `` -> `...6`
• `` -> `...7`
• `` -> `...8`
• `` -> `...9`
• `` -> `...10`
• `` -> `...11`
• `` -> `...12`
• `` -> `...13`
# Write the data to a CSV file
write.csv(cpi_data_excel, file.path(directory,"cpi.csv"), row.names = FALSE)
# Load the CSV file into a data frame
cpi <- read.csv(file.path(directory,"cpi.csv"))
# Read the empty_dwellings file
empty_excel <- read_excel(file.path(directory,"empty_dwellings_by_canton_1999-2023.xlsx"))New names:
• `` -> `...2`
• `` -> `...3`
• `` -> `...4`
• `` -> `...5`
• `` -> `...6`
• `` -> `...7`
• `` -> `...8`
• `` -> `...9`
• `` -> `...10`
• `` -> `...11`
• `` -> `...12`
• `` -> `...13`
# Write the data to a CSV file
write.csv(empty_excel, file.path(directory,"empty_dwellings.csv"), row.names = FALSE)
# Load the CSV file into a data frame
empty_dwellings <- read.csv(file.path(directory,"empty_dwellings.csv"))# Load required libraries
library(ggplot2)
library(plotly)
Attaching package: 'plotly'
The following object is masked from 'package:ggplot2':
last_plot
The following object is masked from 'package:stats':
filter
The following object is masked from 'package:graphics':
layout
library(here)# Load the CSV file into a data frame
properties1 <- read.csv(file.path(directory, "v1_properties.csv"))
properties2 <- read.csv(file.path(directory, "v2_properties.csv"))
# Combine the two data frames
properties <- rbind(properties1, properties2)
# Remove rows with missing values
#properties_without_missing <- properties[complete.cases(properties), ]
# Identify values causing the issue
problematic_values <- properties$number_of_rooms[is.na(as.numeric(properties$number_of_rooms))]
# Replace non-numeric values with NA
properties$number_of_rooms <- as.numeric(gsub("[^0-9.]", "", properties$number_of_rooms))
# Remove non-numeric characters and convert to numeric
properties$price <- as.numeric(gsub("[^0-9]", "", properties$price))
# Subset the dataset to exclude rows with price < 10000
properties <- properties[properties$price >= 10000, ]
# Subset the dataset to exclude rows with numbers of rooms < 25
properties <- properties[properties$number_of_rooms <25, ]histogram_price <- ggplot(properties, aes(x = price)) +
geom_histogram(binwidth = 100000, fill = "skyblue", color = "red") +
labs(title = "Distribution of Prices",
x = "Price",
y = "Frequency") +
theme_minimal()
# Convert ggplot object to plotly object
interactive_histogram_price <- ggplotly(histogram_price)
# Display the interactive histogram
interactive_histogram_pricenote : only price between 0 and 500000 so some outliers aren’t here
# Create the ggplot object
histogram <- ggplot(properties, aes(x = price)) +
geom_histogram(binwidth = 100000, fill = "skyblue", color = "black") +
facet_wrap(~ property_type, scales = "free", ncol = 2) +
labs(title = "Distribution of Prices by Property Type",
x = "Price",
y = "Frequency") +
theme_minimal() +
xlim(0, 5000000)
# Convert ggplot object to plotly object
interactive_histogram <- ggplotly(histogram)
# Display the interactive plot
interactive_histogramnote : only price between 0 and 500000 so some outliers aren’t here
properties$year_category <- substr(properties$year_category, 1, 9)
# Assuming 'year_category' is a column in the 'properties' dataset
properties$year_category <- as.factor(properties$year_category)
# Create a histogram of prices for each year category
histogram <- ggplot(properties, aes(x = price)) +
geom_histogram(binwidth = 100000, fill = "skyblue", color = "black") +
facet_wrap(~ year_category, scales = "free", ncol = 2) +
labs(title = "Distribution of Prices by Year Category",
x = "Price",
y = "Frequency") +
theme_minimal() +
xlim(0, 5000000)
# Convert ggplot object to plotly object
interactive_histogram_year <- ggplotly(histogram)
# Display the interactive plot
interactive_histogram_yearnote : only price between 0 and 500000 so some outliers aren’t here
histogram <- ggplot(properties, aes(x = price)) +
geom_histogram(binwidth = 100000, fill = "skyblue", color = "black") +
facet_wrap(~ canton, scales = "free", ncol = 2) +
labs(title = "Distribution of Prices by Canton",
x = "Price",
y = "Frequency") +
theme_minimal() +
xlim(0, 5000000)
# Convert ggplot object to plotly object
interactive_histogram <- ggplotly(histogram)
# Display the interactive plot
interactive_histogramnote : only price between 0 and 500000 so some outliers aren’t here
and the graph below only show apartments with less than 10 rooms (but you can change the code if needed
# Preprocess the number_of_rooms column
properties$number_of_rooms <- as.character(properties$number_of_rooms)
properties$number_of_rooms <- gsub("\\D", "", properties$number_of_rooms) # Remove non-numeric characters
properties$number_of_rooms <- as.numeric(properties$number_of_rooms) # Convert to numeric
properties$number_of_rooms <- trunc(properties$number_of_rooms) # Truncate non-integer values
properties_room <- properties[properties$number_of_rooms < 10, ] # Filter only number_of_rooms less than 10
# Create a histogram of prices for each number of rooms
histogram <- ggplot(properties_room, aes(x = price)) +
geom_histogram(binwidth = 100000, fill = "skyblue", color = "black") +
facet_wrap(~ number_of_rooms, scales = "free", ncol = 2) +
labs(title = "Distribution of Prices by Number of Rooms",
x = "Price",
y = "Frequency") +
theme_minimal() +
xlim(0, 5000000)
# Convert ggplot object to plotly object
interactive_histogram <- ggplotly(histogram)
# Display the interactive plot
interactive_histogram# Perform multiple linear regression
model <- lm(price ~ number_of_rooms + canton + property_type + year_category, data = properties)
# Summarize the regression model
summary(model)
Call:
lm(formula = price ~ number_of_rooms + canton + property_type +
year_category, data = properties)
Residuals:
Min 1Q Median 3Q Max
-2314382 -559822 -108156 241293 22536934
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 431321.2 131379.4 3.283 0.001032 **
number_of_rooms 1357.6 684.4 1.984 0.047317 *
cantonappenzell-inner-rhoden -143313.8 402840.2 -0.356 0.722031
cantonbasel-landschaft 227183.9 129109.2 1.760 0.078511 .
cantonbasel-stadt 700560.6 155485.5 4.506 6.71e-06 ***
cantonbern -10976.8 127130.1 -0.086 0.931196
cantonfribourg -169186.4 125962.0 -1.343 0.179261
cantonglarus -266743.8 211576.8 -1.261 0.207440
cantonlucerne 350778.4 142862.4 2.455 0.014096 *
cantonnidwalden 492509.1 346376.2 1.422 0.155098
cantonobwalden 616771.6 346124.3 1.782 0.074799 .
cantonschaffhausen -97355.0 166801.2 -0.584 0.559467
cantonschwyz 651288.9 179930.3 3.620 0.000297 ***
cantonsolothurn -232439.8 130615.9 -1.780 0.075186 .
cantonuri 389540.9 218252.9 1.785 0.074330 .
cantonvaud 874966.4 123931.1 7.060 1.81e-12 ***
cantonzug 1408051.0 159937.1 8.804 < 2e-16 ***
cantonzurich 693267.1 128649.1 5.389 7.30e-08 ***
property_typeAttic flat 392966.5 80684.6 4.870 1.14e-06 ***
property_typeBifamiliar house 463159.6 63525.0 7.291 3.38e-13 ***
property_typeChalet 846346.1 107094.0 7.903 3.10e-15 ***
property_typeDuplex 104998.1 78283.7 1.341 0.179878
property_typeFarm house 995929.6 143791.9 6.926 4.67e-12 ***
property_typeLoft 498088.4 459675.6 1.084 0.278591
property_typeRoof flat 9933.7 96105.5 0.103 0.917678
property_typeRustic house 1050378.7 1215025.2 0.864 0.387345
property_typeSingle house 1100195.6 35905.0 30.642 < 2e-16 ***
property_typeTerrace flat 421440.5 143323.8 2.940 0.003287 **
property_typeVilla 1379373.4 64604.0 21.351 < 2e-16 ***
year_category1919-1945 -132783.4 87141.3 -1.524 0.127607
year_category1946-1960 -138372.6 86556.1 -1.599 0.109940
year_category1961-1970 -34994.7 72378.9 -0.483 0.628760
year_category1971-1980 -84239.4 63229.3 -1.332 0.182806
year_category1981-1990 -89926.5 62864.6 -1.430 0.152620
year_category1991-2000 294006.4 66195.6 4.441 9.06e-06 ***
year_category2001-2005 255690.3 76793.1 3.330 0.000874 ***
year_category2006-2010 288423.4 69891.4 4.127 3.72e-05 ***
year_category2011-2015 315433.1 69742.1 4.523 6.19e-06 ***
year_category2016-2022 93644.7 72462.9 1.292 0.196288
year_category2016-2024 263519.5 66575.2 3.958 7.62e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1212000 on 7760 degrees of freedom
(28 observations deleted due to missingness)
Multiple R-squared: 0.2355, Adjusted R-squared: 0.2317
F-statistic: 61.3 on 39 and 7760 DF, p-value: < 2.2e-16